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Record W2197319726 · doi:10.3305/nh.2015.32.1.8819

THE EVOLUTION OF HOME ENTERAL NUTRITION (HEN) IN POLAND DURING FIVE YEARS AFTER IMPLEMENTATION: A MULTICENTRE STUDY.

2015· article· en· W2197319726 on OpenAlexaff
Stanisław Kłęk, Dorota Pawlowska, Grzegorz Dziwiszek, Henryk Komoń, Piotr Compala, Mariusz Nawojski

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsNutrasource
Fundersnot available
KeywordsMedicineParenteral nutritionPercutaneous endoscopic gastrostomyEnteral administrationObservational studyReimbursementGastrostomyPediatricsMulticenter studyFeeding tubeInternal medicineSurgeryRandomized controlled trial

Abstract

fetched live from OpenAlex

BACKGROUND: home enteral nutrition (HEN) is the best option for chronic. patients without the ability to swallow, but with intact digestive tract. Despite the increasing use of home enteral tube feeding (HETF), there is little published information about the types of patients receiving home enteral nutrition. The purpose of this paper to present the evolution of HETF. MATERIAL AND METHODS: the retrospective multicenter observational study was performed using questionnaires, which were distributed among the biggest Polish HEN centres. The study covered all patients treated between January, 2007 and January, 2014. RESULTS: in total 196 adult patients in 2008 (M:104. F: 92, mean age 58.1 [41-75]) and 2842 in 2013 (M: 1541, F: 1301, mean age 61.4 range: 1-91) were assessed. The number of patients grew significantly between 2008 and 2013 (p < 0.05), rising from 196 up to 2 842 (and 1 716 at the moment of study). The predominant primary disease was neurology in both time periods, but the profile switched from neurovascular to neurodegenerative (p > 0.05). Percutaneous endoscopic gastrostomy was the most common GI access ( > 60%), its use and the use of gastrostomies increased significantly since 2008 (p < 0.05). Although the reimbursement for HETF started in 2007, HEN centres expressed doubts about unclear rules for the qualification to HEN and its use. CONCLUSIONS: HETF is a safe, well-tolerated and cost-effective procedure. The profile of patients and techniques may vary at the beginning, but becomes similar to other HETF countries relatively soon. The number of patients grows quickly, and that fact suggests that the prevalence of HETF is similar in all countries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.288
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2015
Admission routes1
Has abstractyes

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